Nonlinear channel modeling and identification using baseband Volterra-Parafac models

Authors:
Thomas Bouilloc;Gérard Favier
Affiliations:
Laboratoire I3S, University of Nice Sophia Antipolis, CNRS, Les Algorithmes - Bít. Euclide B, 2000 Route des lucioles, B.P. 121 - 06903 Sophia Antipolis Cedex, France;Laboratoire I3S, University of Nice Sophia Antipolis, CNRS, Les Algorithmes - Bít. Euclide B, 2000 Route des lucioles, B.P. 121 - 06903 Sophia Antipolis Cedex, France
Venue:
Signal Processing
Year:
2012

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Abstract

Baseband Volterra models are very useful for representing nonlinear communication channels. These models present the specificity to include only odd-order nonlinear terms, with kernels characterized by a double symmetry. The main drawback is their parametric complexity. In this paper, we develop a new class of Volterra models, called baseband Volterra-Parafac models, with a reduced parametric complexity, by using a doubly symmetric Parafac decomposition of high order Volterra kernels viewed as tensors. Three adaptive algorithms are then proposed for estimating the parameters of these models. Some Monte Carlo simulation results are presented to compare the performance of the proposed estimation algorithms, in the case of third-order baseband Volterra systems excited by PSK and QAM inputs.